The invention relates to a method for predicting and/or determining the rollover for a part generated by virtual fine blanking, in which a digital image, in particular the cutting contour of the part, is generated, provided as an image file and subjected to image analysis in an image processing device.
Typical characteristics of fine blanked parts are edge rollover and burr. Rollover develops in particular in corner areas and increases as the corner radius decreases and the sheet metal thickness increases. The rollover depth can amount to approximately 20%, and the rollover width to 30%, of the sheet metal thickness, or more (see DIN 3345, Fine blanking, August 1980). This rollover is thus dependent on the material thickness and quality and can therefore be controlled only to a limited extent, often resulting in impairment of the function of parts, for example due to the resulting change in the functional length of the parts.
Rollover during blanking thus negatively impacts the function of the part and forces the manufacturer to use a thicker starting material.
According to the prior art, information regarding the rollover for part geometries produced by stamping or fine blanking is based on a combination of experimentation and empirical data from cutting and metal-forming processes. The prior art lacks a system for reliably predicting rollover.
Because, at present, the height of the stamping rollover can only be predicted in very vague terms prior to producing the actual parts, the first choice is always a solution involving a starting sheet metal thickness that is relatively high. This notably results in high material consumption and additionally requires greater metal forming forces, whereby, in turn, tooling wear rises.
Known solutions for simulating cutting and metal-forming processes generally employ the finite element method (see DE 10 2006 047 806 A1, DE 10 2007 039 337 B3, EP 923 755 B1, U.S. Pat. No. 6,353,768 B1, U.S. Pat. No. 6,785,640 B1). The drawback of these known solutions is that they are time-consuming, computationally demanding, costly and difficult to apply.